Hidden Markov models (HMMs) provide a powerful framework for inferring unobserved processes that evolve over time or space by linking an underlying Markovian state sequence to observed data via ...

Graphical representations model complex networks by encoding entities as vertices and interactions as edges, with recurring subgraphs—or motifs—revealing fundamental organizational principles. We ...